A model for estimating joint maternal-offspring effects on seed development in autogamous plants

Genotyping of endosperms to determine seed dormancy genes regulating germination through embryonic, endospermic, or maternal tissues in rice

Seed dormancy is imposed by one or more of the embryo, endosperm, and maternal tissues that belong to two generations and represent two ploidy levels. Many quantitative trait loci (QTL) have been identified for seed dormancy as measured by gross effects on reduced germination rate or delayed germination in crop or model plants. This research developed an endosperm genotype−based genetic approach to determine specific tissues through which a mapped QTL regulates germination using rice as a model. This approach involves testing germination velocity for partially after-ripened seeds harvested from single plants heterozygous for a tested QTL and genotyping endosperms from individual germinated and nongerminated seeds with a codominant DNA marker located on the QTL peak region. Information collected about the QTL includes genotypic frequencies in germinated and/or nongerminated subpopulations; allelic frequency distributions during a germination period; endosperm or embryo genotypic differences in germination velocity; and genotypic frequencies for gametes involved in the double fertilization to form the sampled seeds. Using this approach, the seed dormancy loci SD₁₂, SD_1-2, and SD_7-1 were determined to regulate germination through the embryo, endosperm, and maternal tissues, respectively; SD₁₂ and SD_1-2 acted additively on germination velocity in the offspring tissues; and SD₁₂ also was associated with the preferential fertilization of male gametes in rice. This new genetic approach can be used to characterize mapped genes/QTL for tissue-specific functions in endospermic seeds and for marker-assisted selection of QTL alleles before or immediately after germination in crop breeding.

Dissecting genetic architecture underlying seed traits in multiple environments

The seeds of flowering plants develop from double fertilization and play a vital role in reproduction and supplying human and animal food. The genetic variation of seed traits is influenced by multiple genetic systems, e.g., maternal, embryo, and/or endosperm genomes. Understanding the genetic architecture of seed traits is a major challenge because of this complex mechanism of multiple genetic systems, especially the epistasis within or between different genomes and their interactions with the environment. In this study, a statistical model was proposed for mapping QTL with epistasis and QTL-by-environment (QE) interactions underlying endosperm and embryo traits. Our model integrates the maternal and the offspring genomes into one mapping framework and can accurately analyze maternal additive and dominant effects, endosperm/embryo additive and dominant effects, and epistatic effects of two loci in the same or two different genomes, as well as interaction effects of each genetic component of QTL with environment. Intensive simulations under different sampling strategies, heritabilities, and model parameters were performed to investigate the statistical properties of the model. A set of real cottonseed data was analyzed to demonstrate our methods. A software package, QTLNetwork-Seed-1.0.exe, was developed for QTL analysis of seed traits.

Interval Mapping of Quantitative Trait Loci Underlying Triploid Endosperm Traits Using F3 Seeds

A statistical method for mapping quantitative trait loci (QTLs) underlying endosperm traits is proposed. The method is based on a genetic model containing both the direct effects and maternal effects of an endosperm QTL and on an experimental design termed two-stage hierarchical design, in which the trait information is obtained from F(3) endosperms and molecular marker information is obtained from F(2) plants and F(3) embryos (plants). Results of computer simulations indicate that the method can efficiently map endosperm QTLs and precisely estimate both the direct and maternal effects of endosperm QTLs when the sample size is sufficiently large.

A Method for Identification of the Expression Mode and Mapping of QTL Underlying Embryo-Specific Characters

Embryos of crop seeds are one of the major sources of the plant protein and lipid for human nutrition. The genetic expression for embryo-specific characters in crop seeds can be controlled exclusively by the embryo or the maternal genotypes and sometimes by both simultaneously. However, current methods for mapping quantitative trait loci (QTLs) underlying characters of maternal plants have not been effective in dealing with the QTL analysis of embryo characters. On the basis of the expression feature of embryo, a statistical method was proposed for the identification of expression mode and mapping of QTL controlling embryo traits. The maximum likelihood method implemented via the expectation maximization algorithm was used to estimate parameters of a putative embryo-specific QTL. The QTL expression mode was identified by the likelihood ratio test statistic. Statistical power and other properties of the proposed method were investigated under a variety of scenarios through simulation studies. The results showed that the mapping method neglecting the effects of embryo genotype or maternal effects could neither identify the expression mode of QTL nor estimate its genetic effects accurately, whereas the proposed method could effectively map the embryo-specific QTL of various expression modes.